File size: 2,757 Bytes
7cdcc5a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 |
---
library_name: transformers
base_model: CocoRoF/ModernBERT-SimCSE-multitask_v03-distill
tags:
- generated_from_trainer
model-index:
- name: ModernBERT_category
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ModernBERT_category
This model is a fine-tuned version of [CocoRoF/ModernBERT-SimCSE-multitask_v03-distill](https://huggingface.co/CocoRoF/ModernBERT-SimCSE-multitask_v03-distill) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3204
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 32
- total_train_batch_size: 1024
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 15.608 | 0.0444 | 1000 | 0.4726 |
| 14.207 | 0.0888 | 2000 | 0.4257 |
| 12.9331 | 0.1331 | 3000 | 0.4045 |
| 12.5004 | 0.1775 | 4000 | 0.3896 |
| 12.5729 | 0.2219 | 5000 | 0.3786 |
| 12.2146 | 0.2663 | 6000 | 0.3713 |
| 11.8243 | 0.3107 | 7000 | 0.3632 |
| 11.3651 | 0.3550 | 8000 | 0.3578 |
| 11.7742 | 0.3994 | 9000 | 0.3524 |
| 11.022 | 0.4438 | 10000 | 0.3483 |
| 10.871 | 0.4882 | 11000 | 0.3453 |
| 11.24 | 0.5326 | 12000 | 0.3404 |
| 10.6222 | 0.5769 | 13000 | 0.3380 |
| 10.9927 | 0.6213 | 14000 | 0.3354 |
| 10.8912 | 0.6657 | 15000 | 0.3330 |
| 10.7683 | 0.7101 | 16000 | 0.3311 |
| 10.4059 | 0.7545 | 17000 | 0.3286 |
| 10.4617 | 0.7988 | 18000 | 0.3258 |
| 10.5632 | 0.8432 | 19000 | 0.3247 |
| 9.9193 | 0.8876 | 20000 | 0.3231 |
| 9.7854 | 0.9320 | 21000 | 0.3205 |
| 10.3546 | 0.9764 | 22000 | 0.3204 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0
|